In this study, we set up and analyze a cancer growth model that integrates a chemotherapy drug with the impact of vitamins in boosting and strengthening the immune system. The aim of this study is to determine the minimal amount of treatment required to eliminate cancer, which will help to reduce harm to patients. It is assumed that vitamins come from organic foods and beverages. The chemotherapy drug is added to delay and eliminate tumor cell growth and division. To that end, we suggest the tumor-immune model, composed of the interaction of tumor and immune cells, which is composed of two ordinary differential equations. The model’s fundamental mathematical properties, such as positivity, boundedness, and equilibrium existence, are exami

Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning al

Abstract

This paper discusses the essence of the developmental process in auditing firms and offices at the world today. This process is focused on how to adopt the audit concepts which is based on Information and Communication Technology (ICT), including the Continuous Auditing (CA) in particular. The purpose of this paper is to design a practical model for the adoption of CA and its requirements according to the Technology Acceptance Model (TAM). This model will serve as a road map for manage the change and development in the Iraqi auditing firms and offices. The paper uses the analytical approach in reaching to the target results. We design the logical and systematic relations between the nine variable

Face recognition and identity verification are now critical components of current security and verification technology. The main objective of this review is to identify the most important deep learning techniques that have contributed to the improvement in the accuracy and reliability of facial recognition systems, as well as highlighting existing problems and potential future research areas. An extensive literature review was conducted with the assistance of leading scientific databases such as IEEE Xplore, ScienceDirect, and SpringerLink and covered studies from the period 2015 to 2024. The studies of interest were related to the application of deep neural networks, i.e., CNN, Siamese, and Transformer-based models, in face recogni

In light of today's business world, who faces challenges and intense competition as a result of the rapid evolution of technical and informational, organizations had to respond to variables through the adoption of modern management techniques that reduce the effects of risks and activating the role of the internal control system in order to contribute to the early detection of risks and reduce the negative results expected .The research is to address the problem faced by organizations which still follow the traditional methods in the control activities, and the lack of knowledge of the management and their staff of the importance of the existence of risk management and internal control system takes into account these risks, and the limit

Flexible joint robot (FJR) manipulators can offer many attractive features over rigid manipulators, including light weight, safe operation, and high power efficiency. However, the tracking control of the FJR is challenging due to its inherent problems, such as underactuation, coupling, nonlinearities, uncertainties, and unknown external disturbances. In this article, a terminal sliding mode control (TSMC) is proposed for the FJR system to guarantee the finite-time convergence of the systems output, and to achieve the total robustness against the lumped disturbance and estimation error. By using two coordinate transformations, the FJR dynamics is turned into a canonical form. A cascaded finite-time sliding mode observer (CFTSMO) is construct

In the present paper, an eco-epidemiological model consisting of diseased prey consumed by a predator with fear cost, and hunting cooperation property is formulated and studied. It is assumed that the predator doesn’t distinguish between the healthy prey and sick prey and hence it consumed both. The solution’s properties such as existence, uniqueness, positivity, and bounded are discussed. The existence and stability conditions of all possible equilibrium points are studied. The persistence requirements of the proposed system are established. The bifurcation analysis near the non-hyperbolic equilibrium points is investigated. Numerically, some simulations are carried out to validate the main findings and obtain the critical values of th

Humanoids or bipedal robots are other kinds of robots that have legs. The balance of humanoids is the general problem in these types when the other in the support phase and the leg in the swing phase. In this work, the walking pattern generation is studied by MATLAB for two types of degrees of freedom, 10 and 17 degrees of freedom. Besides, the KHR-2HV simulation model is used to simulate the experimental results by Webots. Similarly, Arduino and LOBOT LSC microcontrollers are used to program the bipedal robot. After the several methods for programming the bipedal robot by Arduino microcontroller, LOBOT LSC-32 driver model is the better than PCA 96685 Driver-16 channel servo driver for programming the bipedal walking rob

This paper proposes and studies an ecotoxicant system with Lotka-Volterra functional response for predation including prey protective region. The equilibrium points and the stability of this model have been investigated analytically both locally and globally. Finally, numerical simulations and graphical representations have been utilized to support our analytical findings

The operation and management of water resources projects have direct and significant effects on the optimum use of water. Artificial intelligence techniques are a new tool used to help in making optimized decisions, based on knowledge bases in the planning, implementation, operation and management of projects as well as controlling flowing water quantities to prevent flooding and storage of excess water and use it during drought.

 In this research, an Expert System was designed for operating and managing the system of AthTharthar Lake (ESSTAR). It was applied for all expected conditions of flow, including the cases of   drought, normal flow, and during floods. Moreover, the cases of hypothetical op